1. Field of the Invention
This invention relates to image analysis and, more specifically, to a system and method for identifying objects of interest in image data.
2. Background of the Related Art
Computer-aided image recognition systems rely solely on the pixel content contained in a two-dimensional image. The image analysis relies entirely on pixel luminance or color, and/or spatial relationship of pixels to one another. In addition, image recognition systems utilize statistical analysis methodologies that must assume that the forms of the underlying density (distribution) functions distinguishing the image objects are known (i.e., parametric densities). Classical parametric densities are usually unimodal with a single local maximum distribution of optic characteristics, such as density or color.
However, most real-world image analysis problems involve multi-modal densities, often with distributed low-dimensional densities making identification with existing pattern recognition approaches difficult, if not impossible. The following are some of the specific issues limiting existing image analysis methodologies:
(1) input data (image objects) need to be parametric;
(2) did not adjust for scale, rotation, perspective, size, etc.;
(3) classes of objects need to be statistically distinct in the image;
(4) black and white and grayscale processing is insufficient to identify complex images; and
(5) color processing can be very computationally intensive.